Regression Challenge

Dataset statistics

Number of variables	18
Number of observations	10000
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	210
Duplicate rows (%)	2.1%
Total size in memory	488.4 KiB
Average record size in memory	50.0 B

Variable types

Numeric	4
Categorical	14

Alerts

Dataset has 210 (2.1%) duplicate rows	Duplicates
`para4` is highly correlated with `price`	High correlation
`price` is highly correlated with `para4`	High correlation
`para2` is highly correlated with `price`	High correlation
`para4` is highly correlated with `price`	High correlation
`price` is highly correlated with `para2` and 1 other fields	High correlation
`para2` is highly correlated with `price`	High correlation
`price` is highly correlated with `para2`	High correlation
`para1` is highly skewed (γ1 = 88.1990368)	Skewed
`para1` has 836 (8.4%) zeros	Zeros

Reproduction

Analysis started	2021-10-14 06:40:00.328688
Analysis finished	2021-10-14 06:40:30.581095
Duration	30.25 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

para1
Real number (ℝ_≥0)

SKEWED
ZEROS

Distinct	13
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.3808

Minimum	0
Maximum	337
Zeros	836
Zeros (%)	8.4%
Negative	0
Negative (%)	0.0%
Memory size	88.0 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	1
Q3	1
95-th percentile	3
Maximum	337
Range	337
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	3.500830893
Coefficient of variation (CV)	2.535364204
Kurtosis	8450.146622
Mean	1.3808
Median Absolute Deviation (MAD)	0
Skewness	88.1990368
Sum	13808
Variance	12.25581694
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=13)

Value	Count	Frequency (%)
1	7052	70.5%
3	1613	16.1%
0	836	8.4%
2	268	2.7%
4	164	1.6%
5	51	0.5%
6	6	0.1%
7	3	< 0.1%
9	2	< 0.1%
13	2	< 0.1%
Other values (3)	3	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	836	8.4%
1	7052	70.5%
2	268	2.7%
3	1613	16.1%
4	164	1.6%
5	51	0.5%
6	6	0.1%
7	3	< 0.1%
8	1	< 0.1%
9	2	< 0.1%

Value	Count	Frequency (%)
337	1	< 0.1%
24	1	< 0.1%
13	2	< 0.1%
9	2	< 0.1%
8	1	< 0.1%
7	3	< 0.1%
6	6	0.1%
5	51	0.5%
4	164	1.6%
3	1613	16.1%

para2
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	1016
Distinct (%)	10.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	447.384

Minimum	16
Maximum	2554
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	88.0 KiB

Quantile statistics

Minimum	16
5-th percentile	124
Q1	301
median	434
Q3	582
95-th percentile	775
Maximum	2554
Range	2538
Interquartile range (IQR)	281

Descriptive statistics

Standard deviation	221.0058612
Coefficient of variation (CV)	0.4939958989
Kurtosis	8.07765682
Mean	447.384
Median Absolute Deviation (MAD)	140
Skewness	1.373929782
Sum	4473840
Variance	48843.5907
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
16	93	0.9%
554	73	0.7%
215	59	0.6%
509	54	0.5%
349	52	0.5%
306	49	0.5%
420	40	0.4%
322	37	0.4%
235	37	0.4%
347	36	0.4%
Other values (1006)	9470	94.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
16	93	0.9%
17	6	0.1%
18	9	0.1%
19	11	0.1%
20	6	0.1%
21	8	0.1%
22	6	0.1%
23	13	0.1%
24	6	0.1%
25	15	0.1%

Value	Count	Frequency (%)
2554	1	< 0.1%
2514	1	< 0.1%
2503	1	< 0.1%
2453	1	< 0.1%
2332	1	< 0.1%
2325	1	< 0.1%
2324	1	< 0.1%
2317	1	< 0.1%
2293	1	< 0.1%
2191	1	< 0.1%

para4
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	243
Distinct (%)	2.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	8.459522

Minimum	1
Maximum	27.2
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	88.0 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	4
median	7.2
Q3	13.6
95-th percentile	13.6
Maximum	27.2
Range	26.2
Interquartile range (IQR)	9.6

Descriptive statistics

Standard deviation	4.613526048
Coefficient of variation (CV)	0.545364862
Kurtosis	-1.203979137
Mean	8.459522
Median Absolute Deviation (MAD)	4.4
Skewness	0.1146327091
Sum	84595.22
Variance	21.28462259
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
13.6	3306	33.1%
6.8	437	4.4%
4	426	4.3%
6	350	3.5%
2	278	2.8%
3	226	2.3%
3.2	210	2.1%
2.4	207	2.1%
3.6	197	2.0%
4.4	190	1.9%
Other values (233)	4173	41.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	38	0.4%
1.01	1	< 0.1%
1.1	7	0.1%
1.16	1	< 0.1%
1.2	90	0.9%
1.25	2	< 0.1%
1.3	5	0.1%
1.33	2	< 0.1%
1.35	2	< 0.1%
1.4	9	0.1%

Value	Count	Frequency (%)
27.2	5	0.1%
26.4	5	0.1%
26	2	< 0.1%
25.6	2	< 0.1%
24.8	2	< 0.1%
24	2	< 0.1%
23.2	1	< 0.1%
22.8	2	< 0.1%
22.4	2	< 0.1%
21.6	3	< 0.1%

price
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	932
Distinct (%)	9.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	433.733056

Minimum	50.73
Maximum	5700
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	88.0 KiB

Quantile statistics

Minimum	50.73
5-th percentile	150
Q1	250
median	370
Q3	550
95-th percentile	880
Maximum	5700
Range	5649.27
Interquartile range (IQR)	300

Descriptive statistics

Standard deviation	277.4359467
Coefficient of variation (CV)	0.6396467663
Kurtosis	33.78328466
Mean	433.733056
Median Absolute Deviation (MAD)	130
Skewness	3.619454796
Sum	4337330.56
Variance	76970.70453
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
400	365	3.6%
300	314	3.1%
350	290	2.9%
250	282	2.8%
500	243	2.4%
200	235	2.4%
450	232	2.3%
550	188	1.9%
600	158	1.6%
650	150	1.5%
Other values (922)	7543	75.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
50.73	1	< 0.1%
50.88	1	< 0.1%
51.92	1	< 0.1%
52.3	1	< 0.1%
52.48	1	< 0.1%
54.33	1	< 0.1%
57.72	1	< 0.1%
60	4	< 0.1%
61.03	1	< 0.1%
61.71	1	< 0.1%

Value	Count	Frequency (%)
5700	1	< 0.1%
4600	1	< 0.1%
3800	1	< 0.1%
3590	1	< 0.1%
3550	1	< 0.1%
3500	1	< 0.1%
3170	1	< 0.1%
3080	1	< 0.1%
3050	1	< 0.1%
2900	1	< 0.1%

loc1_0
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	78.2 KiB

0	8514
1	1486

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	1
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	8514	85.1%
1	1486	14.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	8514	85.1%
1	1486	14.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

loc1_1
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	78.2 KiB

0	8777
1	1223

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	8777	87.8%
1	1223	12.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	8777	87.8%
1	1223	12.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

loc1_2
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	78.2 KiB

0	8393
1	1607

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	8393	83.9%
1	1607	16.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	8393	83.9%
1	1607	16.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

loc1_3
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	78.2 KiB

0	9055
1	945

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	9055	90.5%
1	945	9.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	9055	90.5%
1	945	9.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

loc1_4
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	78.2 KiB

0	9227
1	773

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
0	9227	92.3%
1	773	7.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	9227	92.3%
1	773	7.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

loc1_5
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	78.2 KiB

0	9154
1	846

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
0	9154	91.5%
1	846	8.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	9154	91.5%
1	846	8.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

loc1_6
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	78.2 KiB

0	9380
1	620

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	9380	93.8%
1	620	6.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	9380	93.8%
1	620	6.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

loc1_7
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	78.2 KiB

0	8919
1	1081

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	8919	89.2%
1	1081	10.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	8919	89.2%
1	1081	10.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

loc1_8
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	78.2 KiB

0	9273
1	727

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	9273	92.7%
1	727	7.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	9273	92.7%
1	727	7.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

loc1_9
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	78.2 KiB

0	9310
1	690

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	1
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	9310	93.1%
1	690	6.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	9310	93.1%
1	690	6.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

dow_Mon
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	78.2 KiB

0	8082
1	1918

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	1
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
0	8082	80.8%
1	1918	19.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	8082	80.8%
1	1918	19.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

dow_Thu
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	78.2 KiB

0	8092
1	1908

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	1
3rd row	0
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
0	8092	80.9%
1	1908	19.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	8092	80.9%
1	1908	19.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

dow_Tue
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	78.2 KiB

0	8003
1	1997

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	8003	80.0%
1	1997	20.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	8003	80.0%
1	1997	20.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

dow_Wed
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	78.2 KiB

0	7767
1	2233

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	7767	77.7%
1	2233	22.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	7767	77.7%
1	2233	22.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	para1	para2	para4	price	loc1_0	loc1_1	loc1_4	loc1_5	loc1_7	loc1_8	loc1_9	dow_Mon	dow_Thu	dow_Tue	dow_Wed
0	1	662	3.8	73.49	1	0	0	0	0	0	0	1	0	0	0
1	1	340	9.2	300.0	0	0	0	0	0	0	1	0	1	0	0
2	0	16	3.0	130.0	1	0	0	0	0	0	0	1	0	0	0
3	1	17	6.4	365.0	0	0	1	0	0	0	0	1	0	0	0
4	1	610	10.8	357.5	0	0	0	1	0	0	0	0	1	0	0
5	1	483	13.6	550.0	1	0	0	0	0	0	0	0	0	1	0
6	1	214	3.0	210.0	1	0	0	0	0	0	0	1	0	0	0
7	1	452	3.0	366.67	0	0	0	0	1	0	0	0	0	0	1
8	1	130	4.5	193.33	0	0	0	0	0	1	0	0	0	1	0
9	4	1004	13.2	1400.0	0	1	0	0	0	0	0	0	0	0	0

Last rows

	para1	para2	para4	price	loc1_0	loc1_2	loc1_3	loc1_6	loc1_7	loc1_9	dow_Thu	dow_Tue	dow_Wed
9990	1	595	13.6	620.0	0	0	0	0	0	1	0	0	1
9991	4	143	13.6	190.0	0	0	1	0	0	0	1	0	0
9992	0	323	13.6	420.0	0	1	0	0	0	0	0	0	1
9993	0	291	4.0	175.0	0	1	0	0	0	0	1	0	0
9994	1	628	5.2	250.0	0	0	0	1	0	0	0	1	0
9995	3	386	12.0	460.0	0	0	0	0	0	1	0	0	0
9996	1	386	8.0	325.0	0	0	0	0	1	0	1	0	0
9997	0	190	5.6	133.33	1	0	0	0	0	0	0	1	0
9998	3	717	13.6	820.0	0	0	0	0	1	0	0	0	0
9999	1	622	4.8	375.0	0	0	0	0	1	0	1	0	0

Most frequently occurring

	para1	para2	para4	price	loc1_0	loc1_1	loc1_2	dow_Mon	dow_Thu	dow_Tue	dow_Wed	# duplicates
44	1	215	13.6	670.0	1	0	0	0	0	1	0	11
184	3	215	13.6	670.0	1	0	0	0	0	0	0	10
45	1	215	13.6	670.0	1	0	0	1	0	0	0	8
24	0	349	13.6	460.0	0	1	0	0	0	0	0	7
43	1	215	13.6	670.0	1	0	0	0	0	0	1	7
173	1	727	13.6	950.0	0	1	0	0	0	1	0	7
27	0	349	13.6	460.0	0	1	0	0	1	0	0	6
39	1	193	13.6	275.0	0	1	0	0	0	1	0	6
36	1	155	13.6	250.0	0	1	0	1	0	0	0	5
63	1	322	13.6	430.0	0	0	1	0	0	0	1	5

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script